Environmental drivers of shrimp abundance: comparing insights from local ecological knowledge and empirical modeling
Environmental changes in the ocean are increasingly affecting commercially important fishery species. The relationship between environmental parameters and the abundance, distribution, phenology and timing of the reproductive cycles in marine organisms though is often not well understood. Our study...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1589076/full |
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| Summary: | Environmental changes in the ocean are increasingly affecting commercially important fishery species. The relationship between environmental parameters and the abundance, distribution, phenology and timing of the reproductive cycles in marine organisms though is often not well understood. Our study explores the impact of storms, rainfall, temperature, wind and offshore reproduction on two commercial shrimp populations, brown and white shrimp in North Carolina, using a survey among commercial shrimp fishers and a set of quantitative population models that were developed from a long-term biological dataset. We identify multiple overlaps but also differences between fishers' observations and model outputs in particular for the impacts of wind and storms. We further find that fishers mainly rely on their own experience and other fishers to learn about shrimp abundance and less on information provided by fishery managers. Perceptions of environmental drivers were related to livelihood dependency on the shrimp fishery and fishing experience while knowledge seeking behavior was related to fishing experience, the role fishers play in the fishery, and the number of household members engaged in fishing. We discuss implications for shrimp fishery management and discuss challenges of comparing LEK data collected from fishers with modeling outputs including potential differences in temporal and spatial scales. |
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| ISSN: | 2296-7745 |